Autonomous driving requires high accuracy, real-time localization of vehicles. Currently, most vehicle navigation has been accomplished using a global positioning system (GPS), which provides a real-time location with a 95% confidence interval of 7.8 meters, according to the US government. However, in complicated urban environments, reflection in GPS signals can further increase this error, such that a determined location may be off by as much as 30 meters. Given that the width of many lanes is only 3 to 4 meters, this accuracy is not sufficient to properly localize an autonomous vehicle so that it can make appropriate route planning decisions. Other sensors, such as inertial measurement units (IMUs) can increase the accuracy of localization by taking into account vehicle movement, but these sensors tend to drift and still do not provide sufficient accuracy for localization. In general, the industry recognizes that a localization accuracy of around 10 cm is desired for autonomous driving in many areas. Thus, optical and/or image-based techniques for vehicle localization may be used to localize the vehicle to the desired accuracy level. However, optical and/or image-based techniques for vehicle localization generally require conditions with sufficient ambient illumination levels. For example, the set of features that are visible during the daytime may be different from the features that are visible during the nighttime.